{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "round-tolerance",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fuelCost</th>\n",
       "      <th>speed100</th>\n",
       "      <th>horserPower</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.8</td>\n",
       "      <td>9</td>\n",
       "      <td>150</td>\n",
       "      <td>22.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.8</td>\n",
       "      <td>9</td>\n",
       "      <td>150</td>\n",
       "      <td>22.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.8</td>\n",
       "      <td>9</td>\n",
       "      <td>150</td>\n",
       "      <td>25.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.8</td>\n",
       "      <td>9</td>\n",
       "      <td>150</td>\n",
       "      <td>25.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.8</td>\n",
       "      <td>9</td>\n",
       "      <td>150</td>\n",
       "      <td>26.31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  fuelCost speed100 horserPower  price\n",
       "0      5.8        9         150  22.97\n",
       "1      5.8        9         150  22.97\n",
       "2      5.8        9         150  25.23\n",
       "3      5.8        9         150  25.23\n",
       "4      5.8        9         150  26.31"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import LinearRegression \n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.metrics import mean_squared_error,r2_score\n",
    "\n",
    "# 读取数据\n",
    "data = pd.read_csv(\"./data/price.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "critical-taylor",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(14839, 4)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据类型\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "pressing-defendant",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将错误值进行替换.替换成NAN\n",
    "data = data.replace(\"-\", np.nan)\n",
    "data = data.replace(0, np.nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "vanilla-disabled",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 去除NAN数据所在的行\n",
    "data = data.dropna(axis=0, how='any', thresh=None, subset=None, inplace=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "unique-format",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 更改的数据类型\n",
    "data['speed100'] = data['speed100'].astype('float')\n",
    "data['fuelCost'] = data['fuelCost'].astype('float')\n",
    "data['horserPower'] = data['horserPower'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "indonesian-station",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 只取正常数据的前200条分析\n",
    "data=data.head(200)\n",
    "# data = data.sample(n=200, replace=False, random_state=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "intermediate-intent",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 200 entries, 0 to 302\n",
      "Data columns (total 4 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   fuelCost     200 non-null    float64\n",
      " 1   speed100     200 non-null    float64\n",
      " 2   horserPower  200 non-null    float64\n",
      " 3   price        200 non-null    float64\n",
      "dtypes: float64(4)\n",
      "memory usage: 7.8 KB\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fuelCost</th>\n",
       "      <th>speed100</th>\n",
       "      <th>horserPower</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>200.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>200.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.447200</td>\n",
       "      <td>7.562000</td>\n",
       "      <td>248.510000</td>\n",
       "      <td>62.774350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.714895</td>\n",
       "      <td>1.811065</td>\n",
       "      <td>111.483915</td>\n",
       "      <td>53.417985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.100000</td>\n",
       "      <td>3.100000</td>\n",
       "      <td>131.000000</td>\n",
       "      <td>9.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.300000</td>\n",
       "      <td>6.200000</td>\n",
       "      <td>186.000000</td>\n",
       "      <td>31.292500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.200000</td>\n",
       "      <td>7.600000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>48.010000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.100000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>286.000000</td>\n",
       "      <td>73.442500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>14.300000</td>\n",
       "      <td>11.500000</td>\n",
       "      <td>620.000000</td>\n",
       "      <td>434.750000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         fuelCost    speed100  horserPower       price\n",
       "count  200.000000  200.000000   200.000000  200.000000\n",
       "mean     7.447200    7.562000   248.510000   62.774350\n",
       "std      1.714895    1.811065   111.483915   53.417985\n",
       "min      2.100000    3.100000   131.000000    9.450000\n",
       "25%      6.300000    6.200000   186.000000   31.292500\n",
       "50%      7.200000    7.600000   220.000000   48.010000\n",
       "75%      8.100000    9.000000   286.000000   73.442500\n",
       "max     14.300000   11.500000   620.000000  434.750000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据的信息\n",
    "data.info()\n",
    "# 查看数据描述\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "north-minority",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             fuelCost  speed100  horserPower     price\n",
      "fuelCost     1.000000 -0.741827     0.867075  0.847445\n",
      "speed100    -0.741827  1.000000    -0.913400 -0.743569\n",
      "horserPower  0.867075 -0.913400     1.000000  0.867530\n",
      "price        0.847445 -0.743569     0.867530  1.000000\n"
     ]
    }
   ],
   "source": [
    "data.boxplot()\n",
    "plt.show()\n",
    "##相关系数矩阵 r(相关系数) = x和y的协方差/(x的标准差*y的标准差) == cov（x,y）/σx*σy\n",
    "#相关系数0~0.3弱相关0.3~0.6中等程度相关0.6~1强相关\n",
    "print(data.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "representative-divorce",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\miniconda\\lib\\site-packages\\seaborn\\axisgrid.py:2076: UserWarning: The `size` parameter has been renamed to `height`; please update your code.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1209.6x504 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 通过加入一个参数kind='reg'，seaborn可以添加一条最佳拟合直线和95%的置信带。\n",
    "sns.pairplot(data, x_vars=['fuelCost','speed100','horserPower'], y_vars='price', size=7, aspect=0.8,kind = 'reg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "sharp-communist",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "原始数据特征: (200, 3) ,训练数据特征: (160, 3) ,测试数据特征: (40, 3)\n",
      "原始数据标签: (200,) ,训练数据标签: (160,) ,测试数据标签: (40,)\n"
     ]
    }
   ],
   "source": [
    "# 划分训练数据和测试和数据集\n",
    "X_train,X_test,Y_train,Y_test = train_test_split(data.iloc[:,:3],data.price,train_size=.80)\n",
    " \n",
    "print(\"原始数据特征:\",data.iloc[:,:3].shape,\n",
    "      \",训练数据特征:\",X_train.shape,\n",
    "      \",测试数据特征:\",X_test.shape)\n",
    " \n",
    "print(\"原始数据标签:\",data.price.shape,\n",
    "      \",训练数据标签:\",Y_train.shape,\n",
    "      \",测试数据标签:\",Y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ranking-grade",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最佳拟合线:截距 -145.63483467421435 ,回归系数： [10.41193515  5.4541119   0.35955335]\n"
     ]
    }
   ],
   "source": [
    "# 建立线性回归模型\n",
    "model = LinearRegression()\n",
    " \n",
    "model.fit(X_train,Y_train)\n",
    " \n",
    "a  = model.intercept_#截距\n",
    " \n",
    "b = model.coef_#回归系数\n",
    " \n",
    "print(\"最佳拟合线:截距\",a,\",回归系数：\",b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "sought-shareware",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score 0.9292834110873085\n",
      "[ 17.77439897  82.73720454  40.03943237 211.55161997  30.0605088\n",
      "  55.9356814   19.26174594  48.3120981  212.64244236 231.63353376\n",
      "  60.69549551  82.73720454  13.42230326  72.80496013  55.9356814\n",
      "  97.24438477  90.45181249  21.49301957  18.31981016  19.26174594\n",
      "  68.9282403   18.31981016 206.4297981   30.91682403 206.4297981\n",
      "  30.91682403  31.50843013  90.45181249  72.80496013  63.792297\n",
      "  42.1218194   60.15008432  21.49301957  31.50843013  60.69549551\n",
      " 136.00169786  96.69897358  55.09005365   7.15130177  34.76049083]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 获取模型的得分\n",
    "score = model.score(X_test,Y_test)\n",
    " \n",
    "print(\"score\",score)\n",
    " \n",
    "#对线性回归进行预测\n",
    " \n",
    "Y_pred = model.predict(X_test)\n",
    " \n",
    "print(Y_pred)\n",
    " \n",
    "plt.plot(range(len(Y_pred)),Y_pred,'b',label=\"predict\")\n",
    "#显示图像\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "absent-interview",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 对预测结果和测试数据进行观察\n",
    "plt.figure()\n",
    "plt.plot(range(len(Y_pred)),Y_pred,'b',label=\"predict\")\n",
    "plt.plot(range(len(Y_pred)),Y_test,'r',label=\"test\")\n",
    "plt.legend(loc=\"upper right\") #显示图中的标签\n",
    "plt.xlabel(\"the number of price\")\n",
    "plt.ylabel('value of price')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "central-deposit",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
